The heat transfers and fluid flow features of a Microchannel Heat Sink with Secondary Oblique Channels and Rectangular Ribs (MCHS-SOCRR) were examined by numerical and simulation modelling. The adaptive neuro-fuzzy inference system was utilized to predict the Microchannel Heat Sink with Secondary Oblique Channels and Rectangular Ribs heat transfer properties of above-mentioned model using aluminum oxide nanofluid after the modified Dragonfly optimization algorithm approach method was used to establish the optimal geometric parameters for channel width, and relative rib width. At this phase, a comparison of ideal heat transfer and pressure drop values to the present model was made. The validation of the thermal performance is simulated utilizing MATLAB. The significant outcomes of the current study are that the nanoparticle diameter has a significant impact on the temperature of the coolant and the wall. The Nusselt number rises as a consequence of increasing nanoparticles with high thermal conductivity in the system's heat transfer rate. When comparing the two methods, aluminum oxide nanofluid had a faster rate of heat transfer than water. There is evidence that the flow rate of heat through a microchannel is greatly affected by the thermal conductivity of a nanofluid.